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CLASSIFICATION OF T\TEUROMUSCIILAR DISORDERSI BASED ON ELECTROMYOGRAPTTY (EMG) SIGNALS

., Nguyen Hoang Xuan Duy (2012) CLASSIFICATION OF T\TEUROMUSCIILAR DISORDERSI BASED ON ELECTROMYOGRAPTTY (EMG) SIGNALS. Universiti Teknologi Petronas. (Unpublished)

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Abstract

Electromyography (EMG) signals are the measune of activity in the muscles. The motion of the muscles will be generated and recorded using skin surface electrodes. EMG signals can be found from anywhere on the exterior of human's body such as biceps, triceps, shoulder, arm, hand, leg. The aim of this project is to identifr the neuromuscular diseases based on EMG signals by means of classification. The ncuromuscular diseases that have been identified are healthy, myopathy and neuropathy. The signals weIE taken and analyzed from EMG lab database to become datasets for classification system. The classification was carried out using Artilicial Neural Network. In this project, there are two techniques that used to classifr three different types of muscular disorders such as Multilayer Perceptron (MLP) and Wavelet Neural Network (WlIhI). And the input that applied to these systems using feature extraction from EMC signals. In time domain, five feature extraction techniques that used to exmct the sample of signal such as Autoregressive (AR), Root mean square (RMS), Zero crossing (zc), waveform length (wL) and Mean Absolute Value (MA$. The comparison between different techniques will be included based on the accuracy of the result. The input data has been used in Multilayer Perceptron (MtP) to train the classification system. Besides that, frequency domain was used for extracting the useful information from EMG signal for Wavelet neural network (wl[Nr) such as Power Spectrum Density (pSD), both systems were hained and the test performances were examined after training to provide the best result.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 08 Apr 2013 11:17
Last Modified: 25 Jan 2017 09:41
URI: http://utpedia.utp.edu.my/id/eprint/6421

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